Wind power prediction based on improved whale optimization algorithm
Accurate wind power prediction is the basis to ensure the stable operation of wind power grid connection.In order to improve the accuracy of wind power prediction,this paper proposes a new prediction model,firstly,the chaos strategy is used to initialize the population,and the whale optimization algorithm(WOA)is optimized using the Harris Hawk strategy(HHO)with the adaptive weight strategy,and then the improved whale optimization algorithm(HHO-CAWOA)is used to optimize the long and short term memory neural network(LSTM)with the improved whale optimization algorithm(HHO-CAWOA)to optimize the number of neurons and the learning rate,and finally the model is used for wind power prediction.The model has higher prediction performance and better generalization ability and stability than other comparative models.
long and short term memory neural networkwhale optimization algorithmHarris Hawk algorithmwind power prediction
万方数据
维普
